Package: lmtp 1.4.1
lmtp: Non-Parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies
Non-parametric estimators for casual effects based on longitudinal modified treatment policies as described in Diaz, Williams, Hoffman, and Schenck <doi:10.1080/01621459.2021.1955691>, traditional point treatment, and traditional longitudinal effects. Continuous, binary, categorical treatments, and multivariate treatments are allowed as well are censored outcomes. The treatment mechanism is estimated via a density ratio classification procedure irrespective of treatment variable type. For both continuous and binary outcomes, additive treatment effects can be calculated and relative risks and odds ratios may be calculated for binary outcomes.
Authors:
lmtp_1.4.1.tar.gz
lmtp_1.4.1.zip(r-4.5)lmtp_1.4.1.zip(r-4.4)lmtp_1.4.1.zip(r-4.3)
lmtp_1.4.1.tgz(r-4.4-any)lmtp_1.4.1.tgz(r-4.3-any)
lmtp_1.4.1.tar.gz(r-4.5-noble)lmtp_1.4.1.tar.gz(r-4.4-noble)
lmtp_1.4.1.tgz(r-4.4-emscripten)lmtp_1.4.1.tgz(r-4.3-emscripten)
lmtp.pdf |lmtp.html✨
lmtp/json (API)
NEWS
| # Install 'lmtp' in R: |
| install.packages('lmtp', repos = c('https://nt-williams.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/nt-williams/lmtp/issues
- multivariate_data - Simulated Multivariate Exposure Data
- sim_cens - Simulated Longitudinal Data With Censoring
- sim_point_surv - Simulated Point-treatment Survival Data
- sim_t4 - Simulated Longitudinal Data
- sim_timevary_surv - Simulated Time-varying Survival Data
causal-inferencecensored-datalongitudinal-datamachine-learningmodified-treatment-policynonparametric-statisticsprecision-medicinerobust-statisticsstatisticsstochastic-interventionssurvival-analysistargeted-learning
Last updated 17 days agofrom:9bec661967 (on devel). Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 04 2024 |
| R-4.5-win | OK | Nov 04 2024 |
| R-4.5-linux | OK | Nov 04 2024 |
| R-4.4-win | OK | Nov 04 2024 |
| R-4.4-mac | OK | Nov 04 2024 |
| R-4.3-win | OK | Nov 04 2024 |
| R-4.3-mac | OK | Nov 04 2024 |
Exports:create_node_listevent_locfipsilmtp_contrastlmtp_controllmtp_ipwlmtp_sdrlmtp_sublmtp_survivallmtp_tmlestatic_binary_offstatic_binary_ontidy
Dependencies:abindassertthatbackportsbitopscaToolscheckmateclicodetoolscvAUCdata.tabledigestforeachfuturefuture.applygamgenericsglobalsgplotsgtoolsisotoneiteratorsKernSmoothlistenvnnlsorigamiparallellyprogressrR6ROCRSuperLearner
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Create a node list specification | create_node_list |
| Time To Event Last Outcome Carried Forward | event_locf |
| IPSI Function Factory | ipsi |
| Perform Contrasts of LMTP Fits | lmtp_contrast |
| Set LMTP Estimation Parameters | lmtp_control |
| LMTP IPW Estimator | lmtp_ipw |
| LMTP Sequential Doubly Robust Estimator | lmtp_sdr |
| LMTP Substitution Estimator | lmtp_sub |
| LMTP Survival Curve Estimator | lmtp_survival |
| LMTP Targeted Maximum Likelihood Estimator | lmtp_tmle |
| Simulated Multivariate Exposure Data | multivariate_data |
| Simulated Longitudinal Data With Censoring | sim_cens |
| Simulated Point-treatment Survival Data | sim_point_surv |
| Simulated Longitudinal Data | sim_t4 |
| Simulated Time-varying Survival Data | sim_timevary_surv |
| Turn All Treatment Nodes Off | static_binary_off |
| Turn All Treatment Nodes On | static_binary_on |
| Tidy a(n) lmtp object | tidy.lmtp |
| Tidy a(n) lmtp_survival object | tidy.lmtp_survival |
